Sovereign AI on Public Cloud
A white paper by Vishwas Samant
Senior Principal – Architecture
As enterprises scale AI on public cloud, ensuring data residency alone is no longer enough. Prompts, model artifacts, inference outputs, and operational telemetry can cross regional or national boundaries through default platform services, creating risks that traditional cloud governance may not address.
Our latest whitepaper explores how Sovereign Cloud Engineering can help organizations design and operate AI environments with clear controls over sensitive data, models, and workflows. It examines how classification-driven architectures, boundary-constrained AI pipelines, cryptographic controls, and continuous runtime enforcement can protect sovereignty while preserving the benefits of public cloud innovation.
Inside this whitepaper
How telemetry leakage, cross-region model training, inference routing, and third-party dependencies can expose sensitive information.
Explore a reference architecture built around an AI Gateway, Sovereign Control Plane, and sovereignty-aware MLOps framework.
How Sovereign Cloud Solutions can enforce control across data classification, encryption, model lifecycles, monitoring, and operational processes.
How continuous policy enforcement and audit-ready evidence can help organizations maintain regulatory control as AI scales.
Discover how Sovereign Cloud Transformation can enable your organization to balance public cloud innovation with regulatory accountability and operational control, while building AI platforms that can scale with confidence.
Outcreate Your Business
Outcreate with LTM
Outcreate Together
It’s time to Outcreate